Data Manipulation
start_stations <- trips %>%
filter(month(starttime) == 7) %>%
select(name = start_station_name, lat = start_station_latitude,lon = start_station_longitude) %>%
distinct()
end_stations <- trips %>%
filter(month(starttime) == 7) %>%
select(name = end_station_name, lat = end_station_latitude, lon = end_station_longitude) %>%
distinct()
stations <- rbind(start_stations, end_stations) %>%
distinct()
Using ggmap
nyc_map <- get_map(location = c(lon = -74.00, lat = 40.71), maptype = "terrain", zoom = 11)
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.71,-74&zoom=11&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false
ggmap(nyc_map) +
geom_point(data = stations, aes(x = lon, y = lat))
Using leaflet
leaflet() %>%
addTiles() %>%
addCircleMarkers(~lon, ~lat, popup = ~name, radius = 4, stroke = FALSE, fillOpacity = 0.5, color = "navy", data = stations) %>%
addProviderTiles("CartoDB.Positron")
Spatial Join with Pediacities NYC Neighborhood Data
#Downloading the neighborhood data via GET request
r <- GET('http://data.beta.nyc//dataset/0ff93d2d-90ba-457c-9f7e-39e47bf2ac5f/resource/35dd04fb-81b3-479b-a074-a27a37888ce7/download/d085e2f8d0b54d4590b1e7d1f35594c1pediacitiesnycneighborhoods.geojson')
nyc_neighborhoods <- readOGR(content(r,'text'), 'OGRGeoJSON', verbose = F)
## No encoding supplied: defaulting to UTF-8.
stations <- rbind(start_stations, end_stations)
stations_spdf <- stations
coordinates(stations_spdf) <- ~lon + lat
proj4string(stations_spdf) <- proj4string(nyc_neighborhoods)
matches <- over(stations_spdf, nyc_neighborhoods)
stations <- cbind(stations, matches)
station_count <- stations %>%
group_by(neighborhood) %>%
summarize(num = n())
Unique Stations per Neighborhood Using ggmap
plot_data <- tidy(nyc_neighborhoods, region = "neighborhood") %>%
left_join(., station_count, by=c("id" = "neighborhood")) %>%
filter(!is.na(num))
## Warning: Column `id`/`neighborhood` joining character vector and factor,
## coercing into character vector
nyc_map <- get_map(location = c(lon = -74.00, lat = 40.71), maptype = "terrain", zoom = 11)
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.71,-74&zoom=11&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false
ggmap(nyc_map) +
geom_polygon(data = plot_data, aes(x=long, y=lat, group=group, fill=num), alpha=0.75)
Unique Stations per Neighborhood Using leaflet
map_data <- geo_join(nyc_neighborhoods, station_count, "neighborhood", "neighborhood")
pal <- colorNumeric(palette = "RdBu", domain = range(map_data@data$num, na.rm=TRUE))
leaflet(map_data) %>%
addTiles() %>%
addPolygons(fillColor = ~pal(num), popup = ~paste(num)) %>%
addProviderTiles("CartoDB.Positron") %>%
setView(-73.98, 40.75, zoom = 13)
Total Trips From Each Station Per Hour of July 14th
stations_0714 <- trips %>%
filter(date(starttime) == "2014-07-14") %>%
mutate(hour = hour(starttime)) %>%
select(name = start_station_name, lat = start_station_latitude, lon = start_station_longitude, hour)
stations_t_spdf <- stations_0714
coordinates(stations_t_spdf) <- ~lon + lat
proj4string(stations_t_spdf) <- proj4string(nyc_neighborhoods)
matches_t <- over(stations_t_spdf, nyc_neighborhoods)
stations_0714 <- cbind(stations_0714, matches_t)
trip_totals <- stations_0714 %>%
filter(hour %in% c(9, 13, 17, 22)) %>%
group_by(neighborhood, hour) %>%
summarize(num = n())
plot_data_totals <- tidy(nyc_neighborhoods, region = "neighborhood") %>%
left_join(., trip_totals, by=c("id" = "neighborhood")) %>%
filter(!is.na(num))
## Warning: Column `id`/`neighborhood` joining character vector and factor,
## coercing into character vector
nyc_map <- get_map(location = c(lon = -74.00, lat = 40.71), maptype = "terrain", zoom = 11)
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.71,-74&zoom=11&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false
ggmap(nyc_map) +
geom_polygon(data = plot_data_totals, aes(x=long, y=lat, group=group, fill=num), alpha=0.75) +
facet_wrap(~hour)
